https://github.com/edgarogh/camerash

Little educational app to create entropy/randomness from a video input
https://github.com/edgarogh/camerash

android cryptography educational hash random

Last synced: 18 days ago
JSON representation

Little educational app to create entropy/randomness from a video input

• Host: GitHub
• URL: https://github.com/edgarogh/camerash
• Owner: edgarogh
• License: mit
• Created: 2018-05-05T14:27:09.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2024-06-08T17:47:42.000Z (5 months ago)
• Last Synced: 2024-10-15T11:59:54.910Z (about 1 month ago)
• Topics: android, cryptography, educational, hash, random
• Language: Kotlin
• Size: 1.17 MB
• Stars: 1
• Watchers: 4
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Camerash

[![GitHub license](https://img.shields.io/github/license/MrAnima/Camerash.svg)](https://github.com/MrAnima/Camerash/blob/master/LICENSE)

> A simple app that creates randomness from camera frames

![Screenshot](https://github.com/MrAnima/Camerash/blob/master/screenshot.jpg)

## Motivations & Background

In France , for our equivalent to _A Levels_ or _High-School Degree_, one of the exam (TPE - "Tutored Personal Work"), consists of a group work on a specific subject, leading to an oral presentation. Me and my group decided to work on randomness, and among other experiments, like a [double pendulum](https://en.wikipedia.org/wiki/Double_pendulum), I made this app, to show how entropy could be created from a video feed. Given that videos are often influenced by a lot of factors, such as lighting, weather, moving objects or even noise from the camera sensor itself, it's safe to assume that the stream is extremely chaotic. For instance, Cloudflare [uses lava lamps](https://blog.cloudflare.com/lavarand-in-production-the-nitty-gritty-technical-details/) to produce unpredictable cryptographically-secure encryption keys.

## How does it work ?

The camera of the phone captures a video. For each frame:

*   The raw image is acquired as a byte array

*   This byte array is hashed using `SHA1`

*   We take the first byte of the digest and show it in a `TextView`

*   We add all the other bytes to a graph that show the good distribution of numbers

## Release History

*   Be patient. I'm lazy.